Spatial modelling of street-level carbon emissions with multi-source open data: A case study of Guangzhou

Abstract

A refined spatial understanding of carbon emissions is crucial for advancing low-carbon development. This study aims to develop a comprehensive, open data-based approach for spatial modelling of carbon emissions at street level, covering five sectors: industry, transportation, residential & public service, commerce, and agriculture in Guangzhou. Two sets of open data, including statistical yearbook data and urban morphology data, were analyzed using a comprehensive methodology that integrates both bottom-up and top-down approaches to map the spatial distribution of carbon emissions. The findings delineate the carbon emission hierarchy across five distinct sectors as follows: Industrial (37.9%), Transportation (31.3%), Residential (18.6%), Commercial and Public Services (11.6%), and Agriculture (0.6%). The industrial sector emerges as the largest contributor, emitting 61.59 million tons, chiefly situated in suburban industrial zones like Huangpu and Panyu. Following closely is transportation, emitting 50.87 million tons, concentrated around Baiyun International Airport, ports, and urban areas with heavy traffic. Commercial and residential sectors emit 18.94 million tons, primarily within densely populated areas such as Tianhe and Haizhu. Agricultural emissions total 1.02 million tons, predominantly located on the city's outskirts, notably in Nansha. The findings of this study could provide information support for identifying carbon emission hotspots and developing sector-specific low-carbon urban planning strategies.